Techniques for detecting the positions (facial feature point positions) of feature points (facial feature points) of facial organs such as the eyes and the nose from an image in which a face was shot (hereinafter referred to as a “facial image”) and outputting the detected facial feature point positions are important for conducting face direction estimation, face authentication, facial expressions recognition, etc. with high accuracy. A variety of methods have been proposed in regard to the detection of the facial feature point positions.
For example, Non-patent Literature 1 describing a technique for detecting facial feature points and outputting facial feature point positions has disclosed a method for correcting the detected facial feature point positions based on a statistical face shape model. In this method, facial feature points are detected first by applying facial feature point detectors (each of which has been constructed for each facial feature point) to a facial area, and a reliability map indicating the suitability as a facial feature point is generated for each of the detected facial feature points.
Subsequently, for each facial feature point, a facial feature point position having high reliability and minimizing the difference from a position indicated by a statistical face shape model is searched for based on a prescribed evaluation function. In this process, a penalty is assigned (specifically, no weight is assigned) to facial feature point positions that are far from the corresponding position indicated by the statistical face shape model. Therefore, plausible facial feature point positions can be acquired even when part or all of the facial feature points are hidden (blocked) by something in the facial image (obstruction).
Patent Literature 1 describing a technique for detecting facial feature points and outputting facial feature point positions has disclosed a method for correcting the detected facial feature point positions based on geometrical arrangement (positional relationship). In this method, facial feature points in a facial image are searched for first within a preset search area based on inputted reliability maps, by which initial facial feature point positions are acquired as the result of the search.
The initial facial feature point positions acquired by the search are corrected based on their positional relationship, by executing a statistical geometric constraint process employing eigenspaces. Subsequently, the search area is reset based on the corrected initial facial feature point positions and the search for the facial feature point positions is executed again within the reset search area. Finally, plausible facial feature point positions are acquired by judging the positional reliability of the initial facial feature point positions and that of the facial feature point positions as the result of the second search.